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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Molecular Mechanics Simulations and Improved Tight-Binding Hamiltonians for Artificial Light Harvesting Systems: Predicting Geometric Distributions, Disorder, and Spectroscopy of Chromophores in a Protein Environment

We present molecular mechanics and spectroscopic calculations on prototype artificial light harvesting systems consisting of chromophores attached to a tobacco mosaic virus (TMV) protein scaffold. These systems have been synthesized and characterized spectroscopically, but information about the microscopic configurations and geometry of these TMV-templated chromophore assemblies is largely unknown. We use a Monte Carlo conformational search algorithm to determine the preferred positions and orientations of two chromophores, Coumarin 343 together with its linker and Oregon Green 488, when these are attached at two different sites (104 and 123) on the TMV protein. The resulting geometric information shows that the extent of disorder and aggregation properties and therefore the optical properties of the TMV-templated chromophore assembly are highly dependent on both the choice of chromophores and the protein site to which they are bound. We use the results of the conformational search as geometric parameters together with an improved tight-binding Hamiltonian to simulate the linear absorption spectra and compare with experimental spectral measurements. The ideal dipole approximation to the Hamiltonian is not valid because the distance between chromophores can be very small. Finally, we found that using the geometries from the conformational search is necessary to reproduce the features of the experimental spectral peaks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Structure and Orientation of Molecular Wires Embedded in Ultrathin Silica Membrane for Artificial Photosynthesis Elucidated by Polarized FT-IRRAS

Surface sensitive infrared spectroscopic methods are employed for elucidating the structure and orientation of charge conducting molecular wires of type oligo(p-phenylenevinylene) covalently anchored on an ultrathin planar Co oxide catalyst surface and embedded in a few nanometer thick amorphous silica membrane. Comparison of polarized FT-IRRAS with nonpolarized grazing angle ATR FT-IR spectra of nanolayer samples supported on a flat Pt surface and transmission spectra of powder samples showed distinct intensity differences for molecular in-plane and out-of-plane modes that reveal the spatial orientation with respect to the oxide surface. All observations support an upright orientation of the molecular wire axis, which is further confirmed by comparison with IRRAS measurements of physisorbed, horizontally positioned wire molecules. The structural integrity of the molecules is maintained after embedding in the silica membrane by plasma-enhanced atomic layer deposition at 40 °C. The results provide the first spectroscopic evidence of perpendicular orientation of the wire molecules. The complementary surface sensitive infrared measurements by FT-IRRAS and grazing angle ATR FT-IR constitute a powerful approach for elucidating the structure and orientation of surface-anchored molecules and the integrity upon casting into oxide layers such as silica for developing artificial photosystems. Use of the nanolayer construct in IRRAS spectroelectrochemical cell configuration will enable in situ monitoring of the structural and orientation integrity of the silica embedded molecular wires under the sustained electron and proton flux conditions of photocatalytic operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Application of First-Principles-Based Artificial Neural Network Potentials to Multiscale-Shock Dynamics Simulations on Solid Materials

The use of artificial neural network (ANN) potentials trained with first-principles calculations has emerged as a promising approach for molecular dynamics (MD) simulations encompassing large space and time scales while retaining first-principles accuracy. To date, however, the application of ANN-MD has been limited to near-equilibrium processes. Here we combine first-principles-trained ANN-MD with multiscale shock theory (MSST) to successfully describe far-from-equilibrium shock phenomena. Overall, our ANN-MSST-MD approach describes shock-wave propagation in solids with first-principles accuracy but a 5000 times shorter computing time. Accordingly, ANN-MD-MSST was able to resolve fine, long-time elastic deformation at low shock speed, which was impossible with first-principles MD because of the high computational cost. This work thus lays a foundation of ANN-MD simulation to study a wide range of far-from-equilibrium processes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Artificial Neural Networks as Mappings between Proton Potentials, Wave Functions, Densities, and Energy Levels

We report artificial neural networks (ANNs) have become important in quantum chemistry. Herein, applications to nuclear quantum effects, such as zero-point energy, vibrationally excited states, and hydrogen tunneling, are explored. ANNs are used to solve the time-independent Schrödinger equation for single- and double-well potentials representing hydrogen-bonded molecular systems capable of proton transfer. ANN mappings are trained to predict the lowest five proton vibrational energies, wave functions, and densities from the proton potentials and to predict the excited state proton vibrational energies and densities from the proton ground state density. For the inverse problem, ANN mappings are trained to predict the proton potential from the proton vibrational energy levels or the proton ground state density. This latter mapping is theoretically justified by the first Hohenberg-Kohn theorem establishing a one-to-one correspondence between the external potential and the ground state density. ANNs for two- and three-dimensional systems are also presented to illustrate the straightforward extension to higher dimensions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Positive Charge in the Outer Coordination Sphere of an Artificial Enzyme Increases CO 2 Hydrogenation

The protein scaffold around the active site of enzymes is known to influence catalytic activity, but specific scaffold features responsible for favorable influences are often not known. This study focuses on using an artificial metalloenzyme to probe one specific feature of the scaffold, the position of a positive charge in the outer coordination sphere around the active site. Previous work showed that a small molecular complex, [Rh(P Et 2 N glycine P Et 2 )2 ] – , immobilized covalently within a protein scaffold was activated for CO 2 hydrogenation. In this work, using an iterative design where the effect of arginine, histidine, or lysine residues placed in the outer coordination sphere of the catalytic active site were evaluated, we tested the hypothesis that positively charged groups facilitate CO 2 hydrogenation with seven unique constructs. Single-, double-, and triple-point mutations were introduced to directly compare catalytic activity, as monitored by turnover frequencies (TOFs) measured in real time with 1 H NMR spectroscopy, and evaluate related structural and electronic properties. Two of the seven constructs showed a 2- and 3-fold increase relative to the wild type, with overall rates ranging from 0.2 to 0.7 h –1 , and a crystal structure of the fastest of these shows the positive charge positioned next to the active site. A crystal structure of the arginine-containing complex shows that the arginines are positioned near the metal. Molecular dynamics (MD) studies also suggest that the positive charge is oriented next to the active site in the two constructs with faster rates but not in the others and that the positive charge near the active site holds the CO 2 near the metal, all consistent with a positive charge appropriately positioned in the scaffold benefiting catalysis. The MD studies also suggest that changes in the water distribution around the active site may contribute to catalytic activity, while modest structural changes and movement of the complex within the scaffold do not.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Artificial Solid Electrolyte Interphase for Suppressing Surface Reactions and Cathode Dissolution in Aqueous Zinc Ion Batteries

Vanadium-based compounds have been widely used as electrode materials in aqueous zinc ion batteries (ZIBs) due to the multiple oxidation states of vanadium and their open framework structure. However, the solubility of vanadium in aqueous electrolytes and the formation of byproducts during the charge/discharge process cause severe capacity fading and limit cycle life. Here in this paper, we report an ultrathin HfO 2 film as an artificial solid electrolyte interphase (SEI) that is uniformly and conformally deposited by atomic layer deposition (ALD). The inactive hafnium(IV) oxide (HfO 2 ) film not only decreases byproduct (Zn 4 SO 4 (OH) 6 ·xH 2 O) formation on the surface of Zn 3 V 2 O 7 (OH) 2 ·2H 2 O (ZVO) but also suppresses the ZVO cathode dissolution in the electrolyte. As a result, the obtained HfO 2 -coated ZVO cathodes deliver higher capacity and better cycle life (227 mAh g –1 @100 mA g –1 , 90% retention over 100 cycles) compared with pristine ZVO (170 mAh g –1 @100 mA g –1 , 45% retention over 100 cycles). A mechanistic investigation of the role of HfO 2 is presented, along with data showing that our method constitutes a general strategy for other cathodes to enhance their performance in aqueous ZIBs.

25 ENERGY STORAGE↗
DOE OSTI2018

Artificial Metalloproteins Containing Co 4 O 4 Cubane Active Sites

Artificial metalloproteins (ArMs) containing Co 4 O 4 cubane active sites were constructed via biotin-streptavidin technology. Stabilized by hydrogen bonds (H-bonds), terminal and cofacial Co III -OH 2 moieties are observed crystallographically in a series of immobilized cubane sites. Solution electrochemistry provided correlations of oxidation potential and pH. For variants containing Ser and Phe adjacent to the metallocofactor, 1e - /1H + chemistry predominates until pH 8, above which the oxidation becomes pH-independent. Installation of Tyr proximal to the Co 4 O 4 active site provided a single H-bond to one of a set of cofacial Co III -OH 2 groups. With this variant, multi-e - /multi-H + chemistry is observed, along with a change in mechanism at pH 9.5 that is consistent with Tyr deprotonation. Finally, with structural similarities to both the oxygen-evolving complex of photosystem II (H-bonded Tyr) and to thin film water oxidation catalysts (Co 4 O 4 core), these findings bridge synthetic and biological systems for water oxidation, highlighting the importance of secondary sphere interactions in mediating multi-e - /multi-H + reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Controlling Proton-Coupled Electron Transfer in Bioinspired Artificial Photosynthetic Relays

Bioinspired constructs consisting of benzimi- dazole-phenol moieties bearing N-phenylimines as proton-accepting substituents have been designed to mimic the H-bond network associated with the TyrZ-His190 redox relay in photosystem II. These compounds provide a platform to theoretically and experimentally explore and expand proton-coupled electron transfer (PCET) processes. The models feature H-bonds between the phenol and the nitrogen at the 3-position of the benzimidazole and between the 1H-benzimidazole proton and the imine nitrogen. Protonation of the benzimidazole and the imine can be unambiguously detected by infrared spectroelectrochemistry (IRSEC) upon oxidation of the phenol. DFT calculations and IRSEC results demonstrate that with sufficiently strong electron-donating groups at the para-position of the N-phenylimine group (e.g., -OCH3 substitution), proton transfer to the imine is exergonic upon phenol oxidation, leading to a one-electron, two-proton (E2PT) product with the imidazole acting as a proton relay. When transfer of the second proton is not sufficiently exergonic (e.g., -CN substitution), a one-electron, one-proton transfer (EPT) product is dominant. Thus, the extent of proton translocation along the H-bond network, either ~1.6 Å or ~6.4 Å, can be controlled through imine substitution. Moreover, the H-bond strength between the benzimidazole NH and the imine nitrogen, which is a function of their relative pKa values, and the redox potential of the phenoxyl radical/phenol couple are linearly correlated with the Hammett constants of the substituents. In all cases, a high potential (~1 V vs SCE) is observed for the phenoxyl radical/phenol couple. Designing and tuning redox-coupled proton wires is important for understanding bioenergetics and developing novel artificial photosynthetic systems.

Odella, Emmanuel↗
DOE OSTI2019

Listening to the Forest: An Artificial Neural Network‐Based Model of Carbon Uptake at Harvard Forest

Abstract The terrestrial biosphere strongly modulates atmospheric CO 2 mixing ratios, whose inexorable rise propels anthropogenic climate change. Modeling and mechanistically understanding C uptake by the terrestrial biosphere are thus of broad societal concerns. Yet despite considerable progress, scaling up point observations to landscape and larger scales continues to frustrate analyses of the anthropogenically perturbed global C cycle. While that up‐scaling is our overarching motivation, here we focus on one of its elements, modeling C uptake at a given site. We devise a novel artificial neural network (ANN)‐based model of C uptake at Harvard Forest that combines locally observed and remotely sensed variables. Most of our model predictors are those used by an established ecosystem C uptake model, the Vegetation Photosynthesis and Respiration Model (VPRM), easing comparisons. To those, we add observed cumulative antecedent precipitation and soil temperature. We find that model errors are much larger in winter, indicating that better understanding and modeling of respiration will likely discernibly improve model performance. Comparing the ANN and VPRM results reveals errors attributed to unrealistic treatment of temperature in the VPRM formulation, indicating that better representation of temperature dependencies is also likely to enhance model skill. By judiciously comparing VPRM and ANN errors we thus overcome ANNs' notoriety for concealing the mechanisms underlying their predictive skills. We demonstrate their ability to identify outstanding ecosystem science knowledge gaps and particularly fruitful corresponding model development directions, improving site specific and up‐scaling flux modeling and understanding of the climate impacts of the northern forest.

Eshel, Gidon↗
DOE OSTI2020

Indicator Patterns of Forced Change Learned by an Artificial Neural Network

Abstract Many problems in climate science require the identification of signals obscured by both the “noise” of internal climate variability and differences across models. Following previous work, we train an artificial neural network (ANN) to predict the year of a given map of annual‐mean temperature (or precipitation) from forced climate model simulations. This prediction task requires the ANN to learn forced patterns of change amidst a background of climate noise and model differences. We then apply a neural network visualization technique (layerwise relevance propagation) to visualize the spatial patterns that lead the ANN to successfully predict the year. These spatial patterns thus serve as “reliable indicators” of the forced change. The architecture of the ANN is chosen such that these indicators vary in time, thus capturing the evolving nature of regional signals of change. Results are compared to those of more standard approaches like signal‐to‐noise ratios and multilinear regression in order to gain intuition about the reliable indicators identified by the ANN. We then apply an additional visualization tool (backward optimization) to highlight where disagreements in simulated and observed patterns of change are most important for the prediction of the year. This work demonstrates that ANNs and their visualization tools make a powerful pair for extracting climate patterns of forced change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Modeling Ring Current Proton Fluxes Using Artificial Neural Network and Van Allen Probe Measurements

Abstract Terrestrial ring current dynamics are a critical part of the near‐space environment, in that they directly drive geomagnetic field variations that control particle drifts, and define geomagnetic storms. The present study aims to specify a global and time‐varying distribution of ring current proton using geomagnetic indices and solar wind parameters with their history as input. We train an artificial neural network (ANN) model to reproduce proton fluxes measured by the Radiation Belt Storm Probes Ion Composition Experiment instrument onboard Van Allen Probes. By choosing optimal feature parameters and their history length, the model results show a high correlation and a small error between model specifications and satellite measurements. The modeled results well capture energy‐dependent proton dynamics in association with geomagnetic storms, including inward radial diffusion, acceleration and decay. Our ANN model produces proton fluxes with their corresponding 3D spatiotemporal variations, capturing the latitudinal distribution and local time asymmetry that are consistent with observations and that can further inform theory.

Li, Jinxing↗
DOE OSTI2015

Realization of ground-state artificial skyrmion lattices at room temperature

We report that the topological nature of magnetic skyrmions leads to extraordinary properties that provide new insights into fundamental problems of magnetism and exciting potentials for novel magnetic technologies. Prerequisite are systems exhibiting skyrmion lattices at ambient conditions, which have been elusive so far. We demonstrate the realization of artificial Bloch skyrmion lattices over extended areas in their ground state at room temperature by patterning asymmetric magnetic nanodots with controlled circularity on an underlayer with perpendicular magnetic anisotropy (PMA). Polarity is controlled by a tailored magnetic field sequence and demonstrated in magnetometry measurements. The vortex structure is imprinted from the dots into the interfacial region of the underlayer via suppression of the PMA by a critical ion-irradiation step. In conclusion, the imprinted skyrmion lattices are identified directly with polarized neutron reflectometry and confirmed by magnetoresistance measurements. Our results demonstrate an exciting platform to explore room-temperature ground-state skyrmion lattices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Emerging many-body effects in semiconductor artificial graphene with low disorder

Abstract The interplay between electron–electron interactions and the honeycomb topology is expected to produce exotic quantum phenomena and find applications in advanced devices. Semiconductor-based artificial graphene (AG) is an ideal system for these studies that combines high-mobility electron gases with AG topology. However, to date, low-disorder conditions that reveal the interplay of electron–electron interaction with AG symmetry have not been achieved. Here, we report the creation of low-disorder AG that preserves the near-perfection of the pristine electron layer by fabricating small period triangular antidot lattices on high-quality quantum wells. Resonant inelastic light scattering spectra show collective spin-exciton modes at the M-point's nearly flatband saddle-point singularity in the density of states. The observed Coulomb exchange interaction energies are comparable to the gap of Dirac bands at the M-point, demonstrating interplay between quasiparticle interactions and the AG potential. The saddle-point exciton energies are in the terahertz range, making low-disorder AG suitable for contemporary optoelectronic applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Ice rule fragility via topological charge transfer in artificial colloidal ice

Artificial particle ices are model systems of constrained, interacting particles. They have been introduced theoretically to study ice-manifolds emergent from frustration, along with domain wall and grain boundary dynamics, doping, pinning-depinning, controlled transport of topological defects, avalanches, and memory effects. Recently such particle-based ices have been experimentally realized with vortices in nano-patterned superconductors or gravitationally trapped colloids. Here we demonstrate that, although these ices are generally considered equivalent to magnetic spin ices, they can access a novel spectrum of phenomenologies that are inaccessible to the latter. With experiments, theory and simulations we demonstrate that in mixed coordination geometries, entropy-driven negative monopoles spontaneously appear at a density determined by the vertex-mixture ratio. Unlike its spin-based analogue, the colloidal system displays a “fragile ice” manifold, where local energetics oppose the ice rule, which is instead enforced through conservation of the global topological charge. The fragile colloidal ice, stabilized by topology, can be spontaneously broken by topological charge transfer.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Magnetic charge propagation upon a 3D artificial spin-ice

Magnetic charge propagation in spin-ice materials has yielded a paradigm-shift in science, allowing the symmetry between electricity and magnetism to be studied. Recent work is now suggesting the spin-ice surface may be important in mediating the ordering and associated phase space in such materials. Here, we detail a 3D artificial spin-ice, which captures the exact geometry of bulk systems, allowing magnetic charge dynamics to be directly visualized upon the surface. Using magnetic force microscopy, we observe vastly different magnetic charge dynamics along two principal directions. For a field applied along the surface termination, local energetics force magnetic charges to nucleate over a larger characteristic distance, reducing their magnetic Coulomb interaction and producing uncorrelated monopoles. In contrast, applying a field transverse to the surface termination yields highly correlated monopole-antimonopole pairs. Detailed simulations suggest it is the difference in effective chemical potential as well as the energy landscape experienced during dynamics that yields the striking differences in monopole transport.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Deep learning-based segmentation of lithium-ion battery microstructures enhanced by artificially generated electrodes

Accurate 3D representations of lithium-ion battery electrodes, in which the active particles, binder and pore phases are distinguished and labeled, can assist in understanding and ultimately improving battery performance. Here, we demonstrate a methodology for using deep-learning tools to achieve reliable segmentations of volumetric images of electrodes on which standard segmentation approaches fail due to insufficient contrast. We implement the 3D U-Net architecture for segmentation, and, to overcome the limitations of training data obtained experimentally through imaging, we show how synthetic learning data, consisting of realistic artificial electrode structures and their tomographic reconstructions, can be generated and used to enhance network performance. We apply our method to segment x-ray tomographic microscopy images of graphite-silicon composite electrodes and show it is accurate across standard metrics. We then apply it to obtain a statistically meaningful analysis of the microstructural evolution of the carbon-black and binder domain during battery operation.

25 ENERGY STORAGE↗
DOE OSTI2021

String Phase in an Artificial Spin Ice

Abstract One-dimensional strings of local excitations are a fascinating feature of the physical behavior of strongly correlated topological quantum matter. Here we study strings of local excitations in a classical system of interacting nanomagnets, the Santa Fe Ice geometry of artificial spin ice. We measured the moment configuration of the nanomagnets, both after annealing near the ferromagnetic Curie point and in a thermally dynamic state. While the Santa Fe Ice lattice structure is complex, we demonstrate that its disordered magnetic state is naturally described within a framework of emergent strings. We show experimentally that the string length follows a simple Boltzmann distribution with an energy scale that is associated with the system’s magnetic interactions and is consistent with theoretical predictions. The results demonstrate that string descriptions and associated topological characteristics are not unique to quantum models but can also provide a simplifying description of complex classical systems with non-trivial frustration.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Nonlinear multi-magnon scattering in artificial spin ice

Abstract Magnons, the quantum-mechanical fundamental excitations of magnetic solids, are bosons whose number does not need to be conserved in scattering processes. Microwave-induced parametric magnon processes, often called Suhl instabilities, have been believed to occur in magnetic thin films only, where quasi-continuous magnon bands exist. Here, we reveal the existence of such nonlinear magnon-magnon scattering processes and their coherence in ensembles of magnetic nanostructures known as artificial spin ice. We find that these systems exhibit effective scattering processes akin to those observed in continuous magnetic thin films. We utilize a combined microwave and microfocused Brillouin light scattering measurement approach to investigate the evolution of their modes. Scattering events occur between resonance frequencies that are determined by each nanomagnet’s mode volume and profile. Comparison with numerical simulations reveals that frequency doubling is enabled by exciting a subset of nanomagnets that, in turn, act as nanosized antennas, an effect that is akin to scattering in continuous films. Moreover, our results suggest that tunable directional scattering is possible in these structures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗